This course gives you hands-on access to KNIME, a free, open-source, no-code data science platform used to build real machine learning and generative AI solutions without writing a single line of code. You will learn to install KNIME, navigate its visual Workflow Editor, and connect nodes to read, clean, and transform data, building the same core data preparation skills used in professional analytics teams.

From there, you will build and evaluate classification models using decision trees, confusion matrices, and ROC curves, all through drag-and-drop workflows. You will compare multiple models with KNIME's AutoML tools and deploy the model that performs best on your data. The course also introduces generative AI and retrieval-augmented generation (RAG) inside KNIME using only free resources, including a local GPT4All model and the Hugging Face free-tier API, so you can connect a language model to your own data and build a working AI pipeline. Whether you are new to data science or adding no-code machine learning tools to your existing skill set, you will finish this course able to build, evaluate, and explain a complete, AI-powered analytics solution, entirely with free software and no paid subscriptions.